Advanced regression models with SAS and R : California state university, long beach / Olga Korosteleva
Material type: TextPublication details: Boca Raton CRC Press 2019Description: 310pISBN:- 9781138049017
- 519.536 KOR-O
Item type | Current library | Collection | Shelving location | Call number | Status | Date due | Barcode | Item holds | |
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Books | BITS Pilani Hyderabad | 510 | General Stack (For lending) | 519.536 KOR-O (Browse shelf(Opens below)) | Available | 44975 |
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519.536 FRE-R Regression analysis : statistical modeling of a response variable / | 519.536 HIL-J Logistic regression models / | 519.536 HOF-J Linear regression models : applications in R / | 519.536 KOR-O Advanced regression models with SAS and R : California state university, long beach / | 519.536 KUT-M Applied linear statistical models / | 519.536 MAR-P Linear regression : an introduction to statistical models / | 519.536 MAS-L Regression analysis with Python : |
Advanced Regression Models with SAS and R expose the reader to the modern world of regression analysis. The material covered by this book consists of regression models that go beyond linear regression, including models for right-skewed, categorical and hierarchical observations. The book presents the theory and fully worked-out numerical examples with complete SAS and R codes for each regression. The emphasis is on model accuracy and the interpretation of results. For each regression, the fitted model is presented along with the understanding of estimated regression coefficients and prediction of response for given values of predictors. Features: Presents the theoretical framework for each regression. Discusses categorical, count, proportions, right-skewed, longitudinal and hierarchical data. Uses examples based on real-life consulting projects. Provides complete SAS and R codes for each instance. Includes several exercises for every regression. Advanced Regression Models with SAS and Ris designed as a text for an upper-division undergraduate or a graduate course in regression analysis. Prior exposure to the two software packages is desired but not required. The Author: Olga Korosteleva is a Professor of Statistics at California State University, Long Beach. She teaches a large variety of statistical courses to undergraduate and master's students. She has published three statistical textbooks. For a number of years, she has held the position of faculty director of the statistical consulting group. Her research interests lie mostly in applications of statistical methodology through collaboration with her clients in health sciences, nursing, kinesiology, and other fields
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